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Emerging technologies and their impact

Instruction and application
Complete

Now that you’ve explored the latest advancements, it’s time to turn your attention to the emerging technologies shaping the future of ML and AI. Understanding these and their potential impact is key for staying ahead.

  • Trend identification: Recognising technology early gives companies a competitive edge. Agentic AI and small language models are prime examples.
  • Impact assessment: Understanding consequences, such as how edge computing reduces latency for real-time decision-making in logistics.

Agentic AI​

Agentic AI systems have a high degree of autonomy and can take actions without human intervention.

Agentic AI Concept
  • Autonomy: Capable of making decisions in complex environments (e.g., autonomous vehicles, high-frequency financial trading).
  • Ethics: Autonomy brings concerns around accountability—who is responsible for an AI's mistake?

Tip: Trend Analysis Mindset​

When evaluating tech like Agentic AI, focus on:

  • Adoption readiness: Is the infrastructure and regulation ready?
  • Impact assessment: What are the efficiency gains vs. ethical risks?
  • Long-term viability: Is it a passing trend or a game-changer?

Retrieval-Augmented Generation (RAG)​

RAG combines generative models with retrieval models to search through data for relevant info before generating a response.

RAG Architecture

Example: Customer service chatbots can answer a wider range of questions by pulling from a live knowledge base rather than relying solely on training data.

Small language models​

Lightweight versions of traditional large-scale models, designed for efficiency and accessibility.

  • Efficiency: Lower computational requirements make them accessible for companies with limited budgets.
  • Edge AI: Ideal for smartphones and IoT devices, enabling fast, local natural language processing without cloud connectivity.

Edge computing and distributed AI​

Edge computing processes data closer to where it's generated (at the "edge"), reducing the reliance on central cloud servers.

Edge Computing
  • Speed: Drastically reduces latency, which is critical for autonomous vehicles and smart cities.
  • Scalability: Spreads computation across multiple locations, enhancing resilience.

Action item: Pause and think​

Reflect on how these emerging technologies might complement each other in your field.

Questions & Reflections
1. How could AI-driven automation improve operational efficiency in your industry?

Type your reflection here...

2. What ethical challenges do you see in deploying autonomous AI (Agentic AI) in high-risk environments like healthcare?

Type your reflection here...